Inference problems in life testing under multivariate normality

Modified maximum likelihood estimators of the parameters of a multivariate normal distribution are developed when the smallest or largest observations on one of the components are censored. These estimators are used to construct tests for means and correlation coefficients. The robustness of these tests to deviations from normality is investigated.     

Statistical inference and visualization in scale-space for spatially dependent images

SiZer (SIgnificant ZERo crossing of the derivatives) is a graphical scale-space visualization tool that allows for statistical inferences. In this paper we develop a spatial SiZer for finding significant features and conducting goodness-of-fit tests for spatially dependent images. The spatial SiZer utilizes a family of kernel estimates of the image and provides not only exploratory data analysis but also statistical inference with spatial correlation taken into account. It is also capable of comparing the observed image with a specific null model being tested by adjusting the statistical inference using an assumed covariance structure. Pixel locations having statistically significant differences between the image and a given null model are highlighted by arrows. The spatial SiZer is compared with the existing independent SiZer via the analysis of simulated data with and without signal on both planar and spherical domains. We apply the spatial SiZer method to the decadal temperature change over some regions of the Earth.     

Working around the Barriers to Creating and Sharing Knowledge in Capital Goods Projects: the Client's Perspective*

The article considers knowledge management issues from the client's perspective. In the example presented, a sludge treatment centre procured by Northumbrian Water Ltd (NWL), the task faced by the client was to manage knowledge in a context where the core technology being procured was new and resulted in the need for new knowledge to be created and shared both pre‐ and post‐delivery. In exploring these issues, the article reveals the problems of (and some solutions to) managing knowledge across the project life‐cycle and between different groups, where the motivation for generating and sharing knowledge was not the same for all participants.     

Tipping the Multiracial Color-Line: Racialized Preferences of Multiracial Online Daters

Building on previous work on US multiraciality, we analyze the messaging patterns of Asian-white, Hispanic-white, and black-white multiracial heterosexual     

Experimental design for response surface gradient estimation

In this paper, a new experimental design and gradient estimation procedure is presented for Phase I response surface optimization. The design is motivated by basic principles of differential calculus, which imply that if a point in Rⁿ has been reached by exactly minimizing a function along a given direction, then the gradient of the function at that point must be orthogonal to the search direction followed. While exact line search is not required for the new design to be effective, this principle implies that the dimension of the gradient estimation procedure may often be reduced from n to n-1 variables, and the experimenter is able to concentrate experimental effort within the most productive region around the center of the design. The new design and gradient estimation procedures are presented, and bias and variance properties are derived. The effectiveness of the new design is shown to depend on the experimenter's ability to terminate line search within a near-stationary region of the line search function A simple heuristic is presented which indicates whether the new design should be used at a given experimental region.     

Measuring Measurement Error in Economic Time Series

A spectral decomposition method is described for obtaining an upper bound on the amount of measurement error in a time series. The method is applied to generated data and to M1b, real GNP, and the CPI. The bounds provide insight into both the amount of measurement error in these series and the stochastic specification of the errors.